baumhaus.digital/Art, Cognition, Education/Human and Machine Learning/Supervised learning/Features
Features are observable and measurable properties or characteristics used to describe data in both machine learning and human experience.
In ML, features are input variables—raw (e.g., pixel intensities, audio waveforms) or engineered (e.g., embeddings, statistical summaries)—that models use to make predictions.
In human experience, features represent sensory or cognitive details like color, texture, pitch, or emotional tone, helping interpret and navigate the world.
